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Title: Visceral adiposity index (VAI) is related to the severity of anovulation and other clinical features in women with polycystic ovary syndrome. Author: Androulakis II, Kandaraki E, Christakou C, Karachalios A, Marinakis E, Paterakis T, Diamanti-Kandarakis E. Journal: Clin Endocrinol (Oxf); 2014 Sep; 81(3):426-31. PubMed ID: 24601936. Abstract: OBJECTIVE: The clinical phenotype of polycystic ovary syndrome (PCOS) includes reproductive and hormonal aberrations. Visceral adiposity index (VAI) is an indicator which could connect hyperandrogenism and anovulation. The objective was to evaluate the relationship between VAI, menstrual disorders and hormonal, biochemical and ultrasound parameters in women with PCOS. PATIENTS: One hundred and ninety-three women with PCOS diagnosed with Rotterdam criteria. MEASUREMENTS: We correlated VAI with metabolic and clinical features of the syndrome and with indices of inflammation and insulin sensitivity. In addition, we classified the patients into four groups according to the severity of menstrual disorders: Group A (n = 42), with severe menstrual disorders, Group B (n = 83), with mild menstrual disorders, Group C (n = 58), without menstrual disorders and Group D (n = 10) with women with sychnominorroia. RESULTS: In women with PCOS studied, VAI significantly positively correlated with body weight, fasting glucose, insulin, homeostasis model assessment (HOMA) score, white blood cells, platelets, uric acid, free testosterone, oestradiol, total cholesterol, γ-GT, SGPT. Furthermore, a significant inverse correlation between VAI and SHBG, Matsuda index and menstrual cycles per year was documented. From the comparison of the four groups, PCOS women with menstrual disorders had significantly higher VAI and HOMA indices when compared to PCOS without menstrual disorders. CONCLUSIONS: Visceral adiposity index is increased in patients with PCOS in concordance with the severity of anovulation, insulin resistance and inflammation. This index could be a very easy and helpful clinical tool in daily practice to predict insulin resistance in women with PCOS.[Abstract] [Full Text] [Related] [New Search]